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generate_html_report

Renders the last test run results into a self-contained HTML report with embedded screenshots, step list, and test history. Outputs a single file with no external dependencies for easy sharing.

Instructions

把最近一次 run_tests 的結果渲染成單檔自包含 HTML——base64 內嵌截圖、嵌入式 step list、history sparkline 走勢、折疊的 Passed 區塊、展開的 Failed cards。沒外部 CSS/JS 依賴,可以直接寄信、丟靜態 host、貼到 Slack。預設輸出 PROJECT_ROOT/report.html。實作位於 reporters/html.py,走 sample_report.html 同款設計。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputNo選填,輸出檔名(相對於 QA_PROJECT_ROOT)。預設 `report.html`。report.html
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the full burden. It discloses key behaviors: base64 embedding, no external dependencies, default output path, and implementation location. However, it does not mention side effects like file overwriting, potential size issues, or whether it triggers a test run.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph that front-loads the main purpose, then details features and outputs. It is relatively concise for the amount of information provided, though could be slightly more structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (generating a rich HTML report) and no output schema, the description lacks completeness. It does not specify what the tool returns (e.g., success status, file path), when it fails, or how it handles missing test results. The usage context is clear but insufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 1 parameter with 100% coverage (its description is provided). The tool description adds minimal extra meaning beyond the schema, just reiterating the default output path. No additional constraints or usage details are given.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool renders results from the last run_tests into a self-contained HTML report, listing specific features. It distinguishes itself from siblings by its self-contained nature, but does not explicitly compare to get_test_report.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage after running tests ('最近一次 run_tests 的結果'), but does not explicitly state when to use this tool versus alternatives like get_test_report, nor does it mention prerequisites or when not to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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